The problem of extracting airport runway patterns from optical photography has been the subject of study for several years. Nevatia et al. "Linear Extraction and Description", Computer Graphics and Image Processing, Vol. 13, pp. 257-269, 1980 and Zhou et al. "Edge Detection and Linear Feature Extraction Using A 2-D Random Field Model", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. II, No. 1, pp. 84-95, January 1989, are examples of current research in this area. In these works the emphasis is on low level vision computations and little effort is made to isolate the connected components of the airfield. Also, very little work has been done in extracting airport runway patterns from synthetic aperture radar imagery.
Airports represent potential military and law enforcement targets and should be extracted from radar imagery as quickly as possible. This is often difficult because the image data may often be incomplete, cluttered and noisy. Persons trained in pattern recognition are able to extract useable data. However, the work is tedious and time consuming and the results are subject to interpretation. Further, persons engaging in clandestine activities often attempt to camouflage the airfield which makes data extraction even more difficult. This is especially true in attempting to locate small air strips. Automated techniques for extracting specific data from an image involve complex pattern recognition algorithms. However, no known automated procedure is fully adequate to satisfactorily extract airport runway patterns from a radar image.